A Risk Score for Chronic Kidney Disease in the General Population

被引:70
作者
O'Seaghdha, Conall M. [1 ,2 ,3 ,4 ]
Lyass, Asya [5 ]
Massaro, Joseph M. [6 ]
Meigs, James B. [4 ,7 ]
Coresh, Josef [8 ,9 ,10 ,11 ]
D'Agostino, Ralph B., Sr. [5 ]
Astor, Brad C. [8 ,9 ,10 ]
Fox, Caroline S. [1 ,2 ,4 ,12 ]
机构
[1] NHLBI, Framingham Heart Study, Framingham, MA 01702 USA
[2] Ctr Populat Studies, Framingham, MA USA
[3] Massachusetts Gen Hosp, Div Renal, Brigham & Womens Hosp, Boston, MA 02114 USA
[4] Harvard Univ, Sch Med, Boston, MA USA
[5] Boston Univ, Dept Math & Stat, Boston, MA 02215 USA
[6] Boston Univ, Dept Biostat, Sch Publ Hlth, Boston, MA 02215 USA
[7] Massachusetts Gen Hosp, Div Gen Med, Boston, MA 02114 USA
[8] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA
[9] Johns Hopkins Univ, Welch Ctr Prevent Epidemiol & Clin Res, Baltimore, MD USA
[10] Johns Hopkins Univ, Sch Med, Dept Med, Div Gen Internal Med, Baltimore, MD 21205 USA
[11] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Biostat, Baltimore, MD USA
[12] Brigham & Womens Hosp, Div Endocrinol, Boston, MA 02115 USA
关键词
Chronic kidney disease; CKD; Risk score; CORONARY-HEART-DISEASE; GLOMERULAR-FILTRATION-RATE; POSITION STATEMENT; ATHEROSCLEROSIS RISK; SERUM CREATININE; RENAL-DISEASE; PREDICTION; PROGRESSION; HEALTH;
D O I
10.1016/j.amjmed.2011.09.009
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
BACKGROUND: Stratification of individuals at risk for chronic kidney disease may allow optimization of preventive measures to reduce disease incidence and complications. We sought to develop a risk score that estimates an individual's absolute risk of incident chronic kidney disease. METHODS: Framingham Heart Study participants free of baseline chronic kidney disease, who attended a baseline examination in 1995-1998 and follow-up in 2005-2008, were included in the analysis (n = 2490). Chronic kidney disease was defined as an estimated glomerular filtration rate <60 mL/min/1.73m(2) using the Modification of Diet in Renal Disease equation. Participants were assessed for the development of chronic kidney disease at 10 years follow-up. Stepwise logistic regression was used to identify chronic kidney disease risk factors, and these were used to construct a risk score predicting 10-year chronic kidney disease risk. Performance characteristics were assessed using calibration and discrimination measures. The final model was externally validated in the bi-ethnic Atherosclerosis Risk in Communities Study (n = 1777). RESULTS: There were 1171 men and 1319 women at baseline, and the mean age was 57.1 years. At follow-up, 9.2% (n = 229) had developed chronic kidney disease. Age, diabetes, hypertension, baseline estimated glomerular filtration rate, and albuminuria were independently associated with incident chronic kidney disease (P < .05), and these covariates were incorporated into a risk function (c-statistic 0.813). In external validation in the ARIC study, the c-statistic was 0.74 in whites (n = 1353) and 0.75 in blacks (n = 424). CONCLUSION: Risk stratification for chronic kidney disease is achievable using a risk score derived from clinical factors that are readily accessible in primary care. The utility of this score in identifying individuals in the community at high risk of chronic kidney disease warrants further investigation. Published by Elsevier Inc. . The American Journal of Medicine (2012) 125, 270-277
引用
收藏
页码:270 / 277
页数:8
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